Structured documents may be stored in traditional file systems or in databases. With traditional file systems, entire documents are stored. Searching and retrieving data from a large collection of documents is cumbersome. Typically, text based databases provide more flexible and efficient searching and retrieval capability. Object databases and object-relational databases have been used for storing structured documents. Since XML (eXtensible Markup Language) is the most prevalent format for structured documents, many object-relational databases have built-in facilities for handling XML documents. These databases are often referred to as XML-enabled. XML-enabled object-relational databases map the XML data to relational tables and support structural search through their underlying query facilities by reformulating XPath or XQuery expressions to SQL queries. Recently, a number of so called Native XML databases have also been developed for storing XML documents. Native XML databases store the XML data in raw XML or a proprietary format and build indices on elements and attributes to allow fast searching.
With all XML-enabled object-relational databases and some native XML databases, indices are only created on a small number of fields. Searching non-indexed fields is very inefficient. On the other hand, in many native XML databases, all element and attribute names and values are indexed. The large indices make updating such databases of structured documents very inefficient.